3D点云可视化有所不同

Question

我正在尝试在点云上进行一些后期处理， 当我尝试使用Axis3D绘制点云时，我会看到点云的外观不同，它沿轴拉伸。 当我尝试另一个点云视图时，会得到完全不同的网格。

这是我的代码 和图片

def main():

    #process first point cloud
    f3data = np.loadtxt(r'c:\ahmed\Waltersdorf_F3.csv', delimiter=',',
                        dtype=[('id', np.str_, 20), ('x1', np.float32), ('x2', np.float32), ('x3', np.float32),
                               ])


    ptcloud_1 = np.vstack((f3data['x1'], f3data['x2'], f3data['x3'])).transpose()



    pc_1 = pcl.PointCloud.PointXYZ(ptcloud_1)
    X = np.vstack((pc_1.x, pc_1.y, pc_1.z)).transpose()

    import matplotlib.pyplot as plt

    import mpl_toolkits.mplot3d as m3d

    ax = m3d.Axes3D(plt.figure())
    ax.scatter3D(*X.T)
    plt.show()

    # pc_1 = pclpy.radius_outlier_removal(pc_1, search_radius=1.0, min_neighbors=4)
    #plotScatterRot3(f3rot)
    pc_type = utils.get_point_cloud_type(pc_1)
    seg = getattr(pcl.segmentation.SACSegmentation, pc_type)()
    seg.setOptimizeCoefficients(True)
    model = getattr(pcl.sample_consensus, "SACMODEL_" + 'PLANE'.upper())
    seg.setModelType(model)
    seg.setMethodType(pcl.sample_consensus.SAC_RANSAC)
    seg.setDistanceThreshold(1)
    seg.setInputCloud(pc_1)
    coefficients = pcl.ModelCoefficients()
    inliers = pcl.PointIndices()
    arr = np.ndarray(shape=(3,1), dtype= np.float32)
    arr[0] = 0
    arr[1] = 0
    arr[2] = 1
    seg.setAxis(arr)
    seg.segment(inliers, coefficients)

    inla = pc_1.xyz[inliers.indices]

    cloud_filtered = pcl.PointCloud.PointXYZ(inla)
    X = np.vstack((cloud_filtered.x, cloud_filtered.y, cloud_filtered.z)).transpose()


    pca = decomposition.PCA(n_components=3)
    pca.fit(X)
    X = pca.transform(X)
    final_cloud = pcl.PointCloud.PointXYZ(X)

    pcl.io.savePCDFile("original_first.txt", final_cloud)

    import mpl_toolkits.mplot3d as m3d
    ax = m3d.Axes3D(plt.figure())
    ax.scatter3D(*X.T)
    plt.show()

    pptk.viewer(X)

这是数据集

http://www.mediafire.com/file/f8tz1zbpxvyvko7/Waltersdorf_F3.csv/file